Ep. 10 - Supply Chain Mastery: Lessons from Georgia Tech

Supply chain leaders love to ask for “the model,” but the hardest part is figuring out what the real problem is in the first place. We sit down with Georgia Tech professor Benoit Montreuil, Executive Director of the Supply Chain and Logistics Institute, to unpack how his team works with major partners like Amazon, Home Depot, and UPS to tackle frontier logistics challenges with real data, real constraints, and real accountability. 

We walk through what deep industry-academic collaboration looks like when it’s built for long-term impact: fewer partners, stronger trust, and projects that evolve from listening and data analytics into simulation, optimization, and digital twins. Benoit explains how his lab avoids the classic trap of treating every issue like a single-method problem, why scientific rigor and publishing still matter, and how to train PhD students to operate in teams, under NDA, while delivering outcomes that decision-makers can actually use. 

We also get practical about AI in supply chain. Rather than chasing hype, we talk about generative AI as a tool for faster prototyping and experimentation, plus how to manage scope creep with an agile research program and steering committees that can pivot when mission-critical needs appear. Finally, Benoit breaks down the Physical Internet vision: hyperconnected logistics networks where warehouses and transportation capacity are shared like infrastructure, unlocking big gains in cost, resilience, service speed, and greenhouse gas emissions reduction. 

If you care about supply chain strategy, logistics innovation, sustainability, and what the next era of e-commerce fulfillment could look like, this one will stretch your thinking. Subscribe, share this with a colleague, and leave a review, then tell us: what’s the toughest supply chain question you’re facing right now?

Transcript

Welcome And Guest Introduction

SPEAKER_01 0:08

I want to clarify that this podcast is distinct from my responsibilities as a professor in the CMM Walton College of Business. Nonetheless, it aligns with my aspiration to provide practical insights to professionals and business by showcasing companies and people that can enhance your ability to manage, lead, and strategize and market effectively in the retail value chain. And now without further ado, let's get into the exciting episode. I have with me today Benoit Montwe, and he is a professor at Georgia Tech. Benoit, thank you for joining us today. I really appreciate it. It's a pleasure. Thank you.

SPEAKER_00 0:47

Thank you for hosting me.

SPEAKER_01 0:48

Benoit, I you and I um got to spend some time together recently down there at Georgia Tech, and I was blown away um by the center that you're running. Um I know you're executive director of the Supply Chain and Logistics Institute, and also a professor. Um but uh you have a great background, and I know you originally got your PhD from Georgia Tech, um, and now you're back as a professor. How how did that feel to you know get your PhD there and then you know, a few decades later come back as a professor?

SPEAKER_00 1:28

Yeah, that that was an interesting I didn't I didn't count on it. Okay, for me I was kind of a yeah, I'm never gonna be professor there. It's just part of the game. And then around 2013, they began to pick me and and checking and say, listen, we got this chair position, we'd like to for you to come, et cetera. So that that was uh that ended up, it took me a while because I was well established established in in Canada at the Canada Research Chair, and things were going very well. Um, but they were pretty convincing. And at the end at the end, I said, uh, my wife and I we we we said, okay, let's let's go and give it a shot. So I've been there since uh January 2015 now. And I'm really glad it's uh great team here at Georgia Tech. The school is is great, students are great, and professors okay. Uh we have high reputation professors, but with a very good team spirit, so that's really good. So yeah, for me it's good experience. Okay.

Georgia Tech’s New Supply Chain Home

SPEAKER_01 2:27

Well, it's a big difference in weather, that's for sure. And uh, and of course, I know when I was down there, you were just about to move into a new building, and I drove by the I mean the the building you have moved into or about to move into is quite remarkable.

SPEAKER_00 2:47

Oh yes, uh Kate. This is uh this is a very, very interesting move, okay. And uh uh the ISYE uh the school has kind of outgrown our current location where where we are in the main and and is whenever in Gross Lows, and we needed more space. And uh relationship-wise, okay, we have good relationship with the business school, with all the tech companies around and all that. So they decided to move ISYE on the other side of 75, so on the east side of the campus, which is more like IRISE and more township instead of like uh the nice flowers that that I see every day. Okay, but but essentially uh it is really remarkable. We have brand new buildings. They bought they they claimed two new buildings, the George Tower and Shallet Tower. The George Tower will be all of ISYE uh there. And that's where the supply chain logistic institute will have this almost essentially uh one story out of it. Uh and uh and so yeah, it's it's really brand new. The the the atmosphere in the lower part is uh much more open, is really wow, okay, compared to what we have now. It's uh night and day. So it's kind of new generation in uh uh for an industrial and systems engineering department to have such such a building, okay, to uh really leading edge type of building is is really outstanding. So this is the greatest move uh in terms of facilities that we've had. Uh I remember my time where I was in the French building, okay. So I tell you, it's it's not even comparable. Okay, it's a different world now. So yeah, so the all the new generation of professors and students and uh and all of us that have been there for for a while now, they we're just looking uh toward the this as a as a great move.

Building Deep Industry Partnerships

SPEAKER_01 4:41

Uh for those listening, the supply chain and logistics institute at Georgia Tech that Benoit runs is absolutely remarkable. I don't think there's anything like it in the world. Um when you look at the scope uh and depth of supply chain questions, research questions they're addressing for companies, um, it's it's awesome. And I I one thing I loved it about it was it's a clear connection between academia and industry. And on the one hand, it's solving real-world problems, but on the other hand, it's advancing uh theory and understanding of supply chain. I saw that very clearly, and I thought this, I think that's the future of academics. Um, and they're very lucky to have you, Benoit. Um would you mind describing a little bit of maybe giving some examples of uh the kind of supply chain problems you address and also the kind of companies you you deal with? Okay, good.

SPEAKER_00 5:55

So basically, the the way we work with companies is that uh we're we're not trying to have tons of companies and uh have very superficial relationship with companies. So we we're really looking to have companies that will work with as partners, that will have a series of research uh projects with them, we're helping them with recruiting, we're helping them with all kinds of their training and all that. So we have very kind of deep relationships. We know the stuff. We have students that almost get tattooed with uh with the name of company because they work so intensely uh with them. So that's that's really uh at the start, this big point. We care a lot, not much about the fads, but much more about the profound transformation that that is needed to face the new the new challenge and and really addressing the tough questions, the tough uh the what wakes it keeps them awake at night, and and that is like and they know what's gonna shape their future, and that they're not really equipped inside to deal with this, okay, uh uh because they have to get results all the time. And they have teams, so some of the players we're dealing with who can talk about uh Amazon, Home Depot, UPS, uh, and and so on and so forth. Okay, so so those are major league type of players, but still, okay, there are things that they're not really well equipped to address, and that's where we jump in. So we have projects that uh will range with from simple one professor, one student, and some of the projects we're dealing with. Uh we at one point uh we had a project with SF Express in China where we had 20 PhD students and about six professors that were there in a three-year basis. Okay, so we are doing projects with uh MyTech with Warren Buffett Company. Now we're on our sixth year on that on that series of projects uh with them. Uh so that we're we're really going deep and listening to them and not trying to be bigger or smaller. We just try to fit in addressing issues like uh uh with Amazon in the last few years, okay, we went and looked very deeply into the impact of the long tail and the time-sensitive demand and how this would have impact on the deployment uh of the of their networks. Okay, like they went to the regionalization of the of the overall uh network, but then uh okay, that's a move. But then as we as we look even further at how will this have to evolve? Uh, we're looking at the integration between all their fulfillment and all those deployment centers that uh that they have with notions of logistics. Are there's going to be interconnecting? So that and those are for them, this is frontier. Okay, this is stuff that they that is really like a leading edge, and they've got their teams of scientists, but they're interacting uh with us on this stuff. Uh with Tom Depot, we would deal with uh how we they've got millions of clients and how do we source? So clients are asking for something. We said yes, we're gonna give it to you, but where do we source it? Okay, from all the options, the stores that we have, the the fulfillment centers, what kind of means we're gonna use to do this. And and this is flowing like light speed, okay. So there's a lot of it. So we need to make sure we're we're really taking all the options, getting this. We looked at their middle mile network, okay, while we do consolidate things, understanding time sensitivity of clients and and looking at growing their product, the their um performance, their profitability. Uh, we deal a lot on sustainability, uh, green net zero, greenhouse gas emissions, a lot on resilience. But we're not trying to go like one little criteria. We're looking to say, okay, what do you have, what do you think we have to do? What needs to be changing so that that this can improve? And this spans about structure, network design structure, contractual relationship, the the way we're gonna plan operations, etc. So for this, we we we get a lot of data from the people. Many of our students have computers directly provided by the by our partners so they can access data uh on a live basis. And uh no, it's almost full open Q, let's put it this way. So this is this is rich type of setting. So our our teams are are connected with very much the same data that the guys in the company uh have to have access to. So this means that the projects are realistic. So we have like uh 20-some PhDs doing these kind of works right now, for example, and uh all of them deal with company data that comes directly from company large scale, are interacting on a daily, weekly basis, okay, with uh with people in those companies. And uh so in the lab, sometimes you you've been in there, sometimes we end up with five, 10, 20 people from a given company, senior VP going down, and smaller company's CEO and uh and all his team and and working at that the big challenge that they are. So we do a lot of action research, a lot of uh living lab style of research and uh in and driving to solutions that are much deeper than what we did like uh 20 years ago. Uh and it we were basically okay, we're gonna give you a report at the end. We don't do that stuff much, okay? So it's more like getting it to like in the entrepreneurial domain, they would say uh give us a minimum viable product, an MVP, okay, so so that we can really touch it, we can live with uh some of the projects we're dealing right now with, okay. Uh after five years of big development, okay, they're going commercial. We help them like transformative solutions to challenge how they go to business, what they're gonna offer. It's the fit works, okay, gonna transform the industry in that domain. And now we're ending in with them. And after doing a lot of things in lab, in their innovation center, etc., now we're going full blast, okay, uh, on uh uh in in industry, commercializing this. So now helping them. They're they're essentially like launching the production lines, getting all the supply decided, uh thinking all this and this is gonna be happening. So while they do their first round, we're helping them through this. So it's way deeper in terms of technological maturity than and we did. I talk about technological because now we're basically developing with them technologies, okay, that that are leading edge will help on this. So it's kind of a big mixture of math. Okay, so uh I've tried to give you like a simple first shot cover of it. Uh did I answer your questions uh appropriately? Yeah, that was perfect. Yeah.

SPEAKER_01 12:59

Well, you know, I know you and your team have a lot of experience and things like all kinds of optimization, simulation, uh analytical modeling, and really just trying to understand the question, right? That many times uh companies come and they have they have a question that maybe isn't their real question or isn't the real problem. How do you work with that and how do you train your doctoral students to deal with these kinds of things?

SPEAKER_00 13:41

That's an excellent question, okay. So uh it's a fact, okay. So when you've been there that had this stuff for over 40 years, okay, you understand that anybody that comes to you and here's my problem, okay, if you buy that directly, okay, you're a novice, okay? So because it's almost never this, okay. It's just like a symptom where they see, or there's this their perception of it. So we we say first we listen as much as we can, and then we train the student to listen, okay? Ask the right question, listen to the answer, ask more questions, and get them to talk and then explain and really care. Okay, so you need to care. It's not just that you're playing an act. You really have to care and learn that if you want to be in these projects, okay, you better like this stuff, okay, and then make it and invest. So that's the first step. It looks like simplistic, but it's far from simplistic. Okay, because sometimes you have to ask and ask and come back. And and and what we do also is like I told you, we we do a lot of data. So so we data analytics at the beginning, try to make sure we understand. So they talk, and at one point we look at the facts as much as we can, and and already there's there's gaps, okay. One thing they told us, and then what we see is sometimes they're different. So we're we're not trying to come there like as consultants, okay. That's not our worldview, okay. So they're consultants, they do their job. Here, if they come to us, we're we're gonna give them the facts, okay, and we're not trying to get the new contract with them. We're just trying to make sure, okay, that that we're answering those questions and and get them inside. And uh, if we tell them something that they really don't like because we've shaken them, well, too bad, okay. That's it. Okay, so that's that's what we do. But they understand with time that we're we're doing this constructively. So we're gonna do this, okay? But then and then at as we proceed, okay, the the image begins to clarify. Okay, so it's it, and then at one point we begin to not just do analytics. Now now we get in the serious level. We'll develop uh simulation models, we'll develop some uh optimization model to help us see the compromises, we go all the way to digital twins and these kinds of things. And as we progress again, okay, things are gonna change. Okay, and and it things change for many reasons, but one is that uh we know more, they know more. So it's change of perspective. And and then also very important in many products we're dealing with is that we're pushing forward, okay. So what they thought with this, okay, we've addressed this. Now we're we're at another layer. So we're kind of uncovering layers, and now the the questions are different, and and what we have to do are different because we're we're going much more into their reality and pushing, pushing the envelope and it getting them to new capabilities. So that changes a lot. Now I would train the students. Uh the minute they jump in and get with us, okay, uh, we're getting them in projects. Okay, so they're they're involved. So the students going through their courses, but uh one of the prerequisites is listen, you do your courses, but we're gonna get you uh some hours uh working on projects and get get in team or making sure we're coaching them, mentoring them so that they're not dumped into it. They're always we work a lot in teams, okay. So, for example, in the physical internet center, and so everybody's under non-disclosure. Okay, so that the there are things we talk always with companies, so we have to make sure. Uh so but we have many projects. So everybody knows that they can stay in the lab even though there's a meeting considering another project. So they can talk with the other students about this, they can have all kinds of discussions with the professors, but they cannot just begin to talk about this outside the of the confines of the of the center. So that helps a lot because now they see congruence, they see synergies that otherwise they would not do. So we break apart the logic of the one-to-one relationship between a professor, a student, and it's kind of isolated this diet, but much more we're thinking in terms of project themes and the interactions and all that. So that helps them because they learn from the more senior ones and so on. We have the seniors mentoring the new ones. So it's a full ecosystem that we put in place to make sure that we're able to days in, days out, years in, years out, okay, uh, being able to have our partners, industrial partners come in and be able to do research of high caliber with us that will bring high value, high impact on their site. But always we have to be careful though. So the students, okay, must publish teases, much that get their thesis done through this, must have excellent uh results scientifically. They're gonna have to publish three, four papers normally in solid journals on it. And that's part of the game. Okay, the companies know it, and then the students know it, the professors know it, and we're not gonna bend on that. Quality excellence on that level is absolutely mandatory. And at the end it pays off. Okay, the students get their journal papers, and some of them will get into uh academia, some of them will go in industry, some of them will go entrepreneurial. So all kinds of flux that we didn't have in the past. Okay, so that that is now good. And it used to be that, for example, the like the the best students would automatically go to academia. That's not the case right now. So it's kind of a mixture. It's really dependent on the persona, okay? Uh the the the the the values, the and the expectations of of each student, but we're preparing them for the real world, okay? So the if they tell us that's the kind of thing they want, so we just put emphasis to get them in the right direction.

SPEAKER_01 19:34

Benoit, um, you know, I know you have a lot of doctoral students working on this. And to your point earlier, I mean it's great. They they learn how to it probably advances their technical skills. It helps them uh learn how to deal with industry, helps them get uh publications. But I also know from my experience, uh you know, if if they're fairly new and they're say really strong in optimization, then everything's an optimization problem. If they're ever really good in simulation, everything's a similar whatever the whatever it may be. How do you guide them to not see everything as a nail if they've got a hammer?

SPEAKER_00 20:18

I'm not gonna talk for all the professors. I'm gonna talk for me in leading all this and giving an orientation. I talk with them very seriously about this stuff. Okay. I see if you want to come here and you want to advance math programming, okay, and stochastic programming, etc., and it's your first priority, you're probably at the wrong place. Okay. So telling them upfront and understanding what they care about, okay? Because I have some PhD students I've I've been interacting with, and some of my colleagues are interacting with. They're geniuses, okay? They're really, really good, okay. But putting them in projects with industry would be terrible, okay, because that's not their brain, that's not where they are. So we're trying to say it's not for everybody, okay? There are things and you have to learn what it's gonna entail. Is this in line with what you can aspire? Well, and we're gonna test, okay? So we're gonna try things, okay, and see. Now, the the second part is given this, we just say, listen, you're not here to prove to me that you can do optimization or whatever. You're here to help us address those big challenges and learn to work in an interdisciplinary team in which the optimization has a role. Okay. But if I have not defined yet the problem that we have to optimize, okay, it's still fuzzy, then you're gonna lose your time trying to optimize here, okay, because you don't even know what you're gonna be optimizing. If the constraints are in flux, this is not described. So there's work that's been done up front. And sometimes it's not even the problem that's at stake, it's a system that's at stake. The overall context and everything. So we're changing, we're designing a new system, or we're transforming something. So you have to understand that until we've defined the essence of the system correctly, the new system we're playing with, then trying to go too fast to big optimization will aren't. Okay. So that's that's really something that's that's touchy. Okay. So and then the same guys for again, same game for the simulation guys, okay, or gals. So essentially they they jump in there and they see the the full world in terms of simulations. But sometimes I want to what we're trying to do is say your PhD students, understand you'll have two ads. Okay, you've got one at, you're you're gonna be responsible for putting this simulation together. But also you we have to take decisions here, okay? We have to we're trying to get knowledge here. So you're gonna be the experimenter, you have to the the a simulator for me is is a guy where uh to whom to whom we're telling what is our domain model, what is it we want to simulate, and we'll be able to simulate it nicely with good representativity at high speed and giving us the right insight, the right interaction, et cetera. So that's their main goal. But in our kinds of worlds, that's just like half the game, because we're deciding, okay, the network of agents can be involved in this. We're designing uh the algorithms that how they're gonna take their decisions, how they're gonna interact with each other, et cetera. And and that is not simulation. This is systems design, systems planning, systems operations, and and that those are the kind of things we have to constantly play. But at the beginning, frank open discussion with them, putting the rules, rules of the game here, and and making sure that it's not a judgment of value, it's just a questions of fact. You know, in SCL, in the PyCenter, okay, priority is advancing the state of the art and the state of science in supply chain, in logistics, for transport, e-commerce, these kinds of things. Okay, we're all there and we care a lot about this, and we're gonna use whatever artillery is necessary. Like right now, there's a big boost on uh boom on AI. Yeah, we don't do AI for the fun of AI, okay? We just do AI because now it enables us to do things we could not do like a few years back. So so then, but us for us, it's always a tool, okay? So it's always things that help us do do something and not uh oh, let's let's do wow, wow, wow on AI and do all around that AI would transform the world. Everybody knows it's transforming the world. So the key for us is how it's gonna have significant positive impact. So this is goes with our overall philosophy. So that's why whether you're simulation, your AI, your machine learning, your your optimization, your statistics, your whatever, okay, good tools, okay? Let's use your brain now.

Using AI Without Chasing Hype

SPEAKER_01 25:06

Um, speaking of the AI tool since you brought it up, and I I like your philosophy about how it fits into the whole package. Um, it's a tool. It's a great, great way to do it. For that tool, um, you know, it can help you set up an optimization problem. It could probably help you think through what kind of tools should I use to solve this problem. It can help you program, it can even help with analytical modeling and solving. Um I've even been surprised at its ability to do discrete event simulation and and various things. Do I and I I'm wondering, I would suppose that the doctoral students tend to be young. And so you probably don't have to nudge them to to use it as a tool, right? They they probably lean towards it, or do you?

Preventing Scope Creep With Agile

SPEAKER_00 26:06

I think we do, okay? Because like you said earlier, sometimes they come in, they've done optimization all their life, okay? And then you're talking to them about gen AI, okay, gen tick AI, etc. Whoa, what kind of sorcery magic type stuff you're talking to me about? Okay, so that for some of them, it's not the first degree logic. But then you've got many of the others that are tinkerers, okay? They've always played with a bunch of stuff, so it just becomes the new toy, okay. The new not toy, but uh the new the new place to explore and take advantage. And I'm encouraging them a lot on those lines. So I had one of our grad students, master, I talk so often in PhD, but we got a bunch of master students, and one of my master students came to me and he was within a course I'm uh I'm giving it they have to do projects, and he came to me like yesterday and he was presenting to me the idea of a project, okay? It's just the idea of the project. But the guy said, I just use ChatGPT and uh and use this. Uh I succeeded to do like an early concept simulation of it. And he was explaining to me, okay, through this ChatGPT that he had done a few years a few hours ago, okay, and leveraging with the simulation. Okay. And what he was doing was pretty smart. Okay. Years ago, years ago, meaning last year, two years ago, okay, I mean, I would have nobody doing capable of doing anything like this. And now it's become like, yeah, piece of cake. Okay, it was not really tough. Okay. I didn't try to do everything, but just enough to be able to show you. And he clearly succeeded. Okay. So I said, yeah, man, green light, this is a great idea. And uh, yeah, we should work on this stuff. So to me, that's that's really the the sweet spot. Okay, is when when they begin to know enough and have the the intellect to to be curious, okay, to go for it. So it's clear that that sometimes in teams and that we're working in, I'll do some some speech, some pep talk. I can say, listen, okay, uh you have the the big time, you got a chance, okay, of happening at one of the key turning points, induction point, inflection point where where basically uh AI is kind of changing from something esoteric or just like robotics and and these kind of early on, okay. But now it's kind of uh capable of solving things. So gosh, jump into it and making sure that it's gonna be there. So when I was young, okay, uh, I was like the my thesis was interactive optimization facilities layout, okay? So it was a mixture of leveraging deep knowledge in facilities layout, leveraging new new theory in graph theory, in the B matching, network flow, these kind of things, but the latest models and leveraging the fact that we were for the first time having color graphics computers with light pins, interactive, and that I could connect my microcomputer with the mainframe in the back, okay, and I didn't talk. Okay. That was core of what I was doing. I say, what you guys is orders of magnets are much more uh intriguing and potential. So gosh, don't wait for me to tell you everything. Surprise me, go for it, okay? Because this is the new trend, okay? So this is not just a trend, this is the new capability. Go and drive. So you see, I'm I'm I'm trying to say, yes, you're gonna have courses, yes, I can have some technical guys come in and try to help you, but that's not what I'm expecting. I'm expecting new darn. Get the I'll pick the softwares you want to use, okay, the platform. You know, just go and begin to use it. And and when you've tried something, ask yourself whether would this stuff help me do what I want to do? And then as they explore, as they think around to this, then more and more they get confident. Sometimes it's big failures, but sometimes it's great success. We we we had some recent things that said, oh, that stuff I like. I like that very much. So and I then what I do is uh make sure that it's exposed to all my other students, again, our other students at SEL, like in the Pi Center, so that they know that this is fun stuff, and then I'm praising it so to so that it's kind of a positive reinforcement akin to it. But I think that's part of our roles. Okay, we we have to to help them grow and become much better than we are in the future. They're the people that are gonna shape the next 20, 30, 40 years, okay. So I want to make sure that they're not sitting under vacant, okay, that they're really gonna be moving forward, not be a victim of uh or slave of AI. I want them to dominate AI, okay, and do have AI do some things that will, when they're gonna present what they do to industry, to governments, to academia, they're gonna look at this and say, oh my God, okay, those guys are are way up there, okay. This is really, really interesting what they're doing, etc. So that's the way I'm trying to go with all the AI movement.

SPEAKER_01 31:12

So, Benoit, when you have these impressive companies in, and I I really like your approach of hey, you don't want all companies in the world, you you want some set that will be long-term partners that you trust them, they trust you, you can communicate. But but even when you've got those kinds of relationships, one challenge always in these kind of problems is scope creep. You know, people ask for X, but they really want X plus Y, but they don't know the way they've stated the problem, they're not including that. How do you manage that? That's a challenge.

Academia Plus CTO Experience

SPEAKER_00 31:54

Yeah, so we we've developed a new way of dealing with uh how we sign in with companies, okay? So we've got this new statement of works that we're doing that are all about like kind of agile, okay, type of research program, okay, that we're dealing with them. So we oftentimes in more the bigger project where it makes sense, okay, we have this committee, this steering committee, and we make the steering committee sovereign into allowing shift in in what we're gonna look at. The key is that listen, I'm not gonna do more than what you you pay me in terms of resources, okay? I'm not, I'm not, they're not infinite resources. So either they work on this, they work on something else. So we allow ourselves to be highly flexible. Okay, so this is a big, big thing that has changed, okay, before. So we're not telling, okay, here's what you want, we're gonna come back, okay, and by in six months and give you answers, or in a year, or so whatever, and give you a report. No, no, no. It's not the way we're doing it. So things are we're we're working with them, we're learning, like I mentioned earlier, we're getting into actions, we're discovering. Let me give you a case, okay? We were in such a project with a pretty good thing. I think we had eight, eight PhD and master's students, okay, and a number of uh professors involved with uh with a major company. It was through COVID. Already we're very glad because the company kept wanting to have such projects uh during COVID. But then at some point, it was we had been at it for four or five months, and they come back to us and say, listen, Benoit, okay, we like very much what you're doing, and you we we know the competency, the expertise of your group. And can you help us? Because we have a major problem, okay, that that is popping up in our face. While the other one is nice to have, this one is like kind of mission critical. We need to to be able to address this stuff. So basically, we completely switched like 90 degrees, okay, it's even more than 90 degrees, what what the project could be about. But the expectations, though, we we said that we agree on both sides. The reasoning that they had and the what they had as challenge was okay. So we work, we're we're there, we don't deal with companies as they are our clients, they are our partners. Okay. So so it means that it has to be win-win. Because if it's not win-win, I'm not gonna get the smart professors with us. The reason the smart research scientists will not want to be in. The PhD students will have the the ones that are looking for a job and not the ones that are really the the the really spark. At Georgia Tech, we have great PhD students, but there's always people that are like at the top of the P the apex, and you've got others that are solid. But to get the ones over there, you need to have good conditions. Okay, and they and so we need to make sure they understand that. And we tell this at the beginning, and we're never we're not very shying away from this, okay. So, and then when it gets that, it's becoming not at all what we signed up for, etc. So we tell them in and it it may finish, we're gonna finish what we promised, but we're not gonna renew. Okay, it happens very rarely, but we're it's talking the talk, walking the walk on this, okay? It's it's very important. But now the companies we deal with, they know about it. So scope creeping is will be almost everywhere. But we're always coming back and say, listen, do you want us to push there? Okay, this I agree with you, it's interesting, but would I like to finish what we've started because if we just keep always changing, never finishing, you're never creating value. So you need to make sure that yes, we've accomplished this and say, now let's go next step. So we're constantly using this agile type of project management for the kind of things we're doing. So to enable ourselves to adjust, but at the same time be very open with them and say, listen, you can have the bottom and the money from the bother. Okay, so you need to make sure that we make choices. So, for example, some companies uh uh they say this year, yeah, I'm very tight on funds, et cetera. So say, okay, that's fine, we can contrast, but what do you want us to remove from the scope? Okay, because I cannot do everything that we were intending to do with half the amount. Okay, so so so that that's a simple example, but this will come in. So it's kind of uh being managing the relationship. It's like in many organizations, it's managing the account. Okay, so for us, it's managing the organizations, our partners, so that uh we are as transparent as possible with them, okay, and uh also reactive. And we don't let slip situations that's at the beginning could be very small, but since we don't solve them, they become big stuff to try to address them. And and honestly, doing all this, the scope creeping is not at all one of our big troubling issues. It could be, okay? If we didn't do what I've just told you, it would be. But right now, I'd say that's not been an issue. That's great.

SPEAKER_01 37:18

Um now, after you got your so you have experience both as a academic and as a practitioner. Uh, because at some point after your doctorate, you also were a chief technology officer of a company. I would think that kind of um mixture of experience helps you a lot with what you're doing now, is that right?

SPEAKER_00 37:42

Oh yes, okay. I could not do what I'm doing here if I didn't add that kind of eclectic type of experience. Okay, so uh um I started it when I was very, very young. I was at the University of Quebec in Parvia, and uh the we all the students had to do senior design. So I ended up like supervising tons of senior senior design projects with industry. And even though I was young, I was I I got to like this stuff and be good at it. So a bunch of students coming in. So I had I was exposed to many, many contexts, and that gave me confidence. Uh my research was not in something that was kind of very esoteric theoretically, so it was grounded, so it's the designing facilities, etc. So uh, so I got sometimes I would give conference uh presentation conference, and uh, I remember once, okay, uh, we had people from Ford Motor Company that that were there. They waited until the end, and at the end, I say, hey man, uh, we like what you've been presenting, but uh you want to put your mouth, your your money where your mouth is, a kid, you want to to really get there. And what they offered me is that they had just done done transforming uh one of their big plants somewhere in the world, and they would have wanted to see if they would apply their ways of doing what it would have changed. Okay. So, okay, let's try give it a shot. So I got a grad student myself, and we just it was compact, okay, but it was kind of impressive. Okay, they flew me to to uh to uh their born, okay. And then uh I was at the time, this is the kind of we do now. At the time, it was rare, okay. So I was flew to be able to do this video conference with the people from that country. There was about 20 engineers that were there, and then we explained that stuff. They gave me all this stuff. So they said, okay, give us a couple two, three weeks. So we it was so we did it and came back, and they liked it very much. Okay, they liked it. We saved them huge. And they said, Oh my god, we should have had you. So this got me okay in the spiral, okay, of telling companies that that company, okay, and many contracts with them, okay, many places, and and always put on a tough spot in leveraging the our theories, our methods to do this. So that started a small consulting business, okay, that grew into reasonable, okay. So uh uh in terms of consulting. But at one point I got bored and I said, listen, okay, uh, I we're repeating a bunch of things. So now I want to make sure that we were developing technology to help them, okay, try to solve that. So we we got like venture caps into it, we grew it, and we had products all around. So in that I I kept doing this kind of stuff for uh I think 15 years, okay. So uh of doing my full-time job, okay, uh at the university with uh with the courses, the research, the students, and everything, okay, and making sure I would it would be excelling on this, at the same time working, okay, uh at solving this, then grew the team and grew the the leaders into this. Then I said, okay, I've had enough for a while. Okay. It's a company was sold, etc. So, and then and and then basically uh then I I got to be leading uh a lot of research centers and uh and then grew this grew on me and this so got experience along those those those sides and uh and then getting to Georgia Tech, okay. Uh before that I had the research chairs, etc. So all this stuff, okay, and and always connecting with industry and all that. And uh I kept I kept some advising, some circle networks, I was interacting with them. So I've done that all my life, okay. And so and learning to deal with the major league players, and it started small decades ago and then growing. And so now it's it's kind of for me, it's kind of a second nature. And what I'm trying is to take all that stuff and that learning that took me 40-some years to learn and try to make sure that our students, our colleagues, okay, can leverage this and and not have to spend 45 years to reach the right level. So so that's basically the logic. But your point is good, and I think you had such kind of an eclectic type of parkour, and those are good, okay. I think so or somehow. Because if you always just did one thing, for some people it's perfect, okay. But for me, I would not be who I am, okay, if I had such an easy parkour.

SPEAKER_01 42:30

You've also done a lot of work in the physical internet. Um I think many of our listeners have heard of that, but they may not know what it means. Would you mind explaining it and talking a little bit about it? So how many hours do you have?

SPEAKER_00 42:46

No, joking. Uh so basically, uh this started because the the Economist magazine, okay, in 2006, uh had one one one of their issues, the title with the physical internet, and then they had like a state of the art of logistics, etc. So, and I was going to be on a plane for six, seven hours, so I began to read this, and at the end I said, man, this ain't I understand the internet. What they show is nice, but it's not the physical internet, which instead of moving bytes, okay, now we're gonna move atolls, we're gonna move physical objects and and store them, etc. So I spent a number of years after that is trying to say, see, okay, what would be really a physical internet? So use the metaphor, the digital internet, but use it for real physical objects rather than just moving information. So that's how it started. So at the core it is. So now it has grown much, much more. Now we've we've the concept has been highly elaborated, okay. Uh it's been published uh in the last decade. We've published over like 170 papers and in this kind of stuff. Okay, it's been uh going all across. The world now we have entire like the European Union has made the physical internet its vision and in the build roadmap to to get all of Europe implementing these concepts. And build on the interconnection, we call it hyperconnectivity, okay, and and try to make sure that we are giving open access to shit to resources. You know that there are 500,000 uh warehouses in the US. Okay. Yeah, that's the kind of numbers that we have. Most of them are used by one company.

SPEAKER_01 44:53

Okay.

SPEAKER_00 44:54

Most companies, okay, are just having like infull of maximum of facilities, warehouse facilities that they're leveraging. In physical internet, our goal is to say, no, no, they're all going to be available. Some of them just 10% of the time, some more. But now imagine that instead of trying to serve your clients and you just have like a few places, what you can do when you can deploy for the same rough cut, okay, essentially cost the sorry. Uh, you now you can uh deploy in hundreds or even thousands of facilities. Thousands of facilities look crazy to you, but when we get into this new era of quick commerce, okay, where you need to be able to deliver in 20 minutes, okay, you need many facilities. If you try to own this, okay, you're never big enough. Okay. So you need to play with others, okay? So even giants like Amazon, okay, they have 150 type uh facilities in the US, okay. Well, many a lot of the stuff that is in there is not their own. Okay. It's all from all kinds of vendors, okay, that are just using their facilities. So physical internet is on moving the goods, deploying the goods, realizing them, how we're gonna make them, how we're gonna supply them, how we're gonna design them, and how we're going to use them so that we're gonna maximize our potential for asset resource sharing, as well as open flow consolidation, so that we can satisfy the demand for physical objects broadly, okay, uh, in a way that is much more sustainable, economical, uh, uh in economical, environmental, societal level, uh uh much more resilient, much more efficient uh overall. So it's in and we're trying to get order of magnets of improvement. So it's a big deal. And then what we this is looks huge, and it is huge, okay. So there, but then we're trying to show a single company what it's gonna mean for you if you're a logistic service provider, if you're an e-commerce player, so if you're if you're an hospital, etc. So all these and show how it's gonna change your world. And so with this uh eye interconnection and leveraging a lot of the intelligence that we can display now to leverage with all those degrees of freedom that we're trying to get to get to the industry and society. So it's uh I can go on, okay. But that's the spirit of what we're trying to do. And the results are uh are there, okay. We get like uh efficiency, okay. We get easily cost reduction by 20, 40 percent, we get uh greenhouse gas emission by the same kind of numbers when we're combining the the way we change transportation and the way we were changing how we deploy products, we get 40, 50, 60 percent improvement. So the numbers are not like one two person, it's always major league type of things, either if you think of it as a physical intranet within one company or one territory, et cetera, or one industry, or if you go more like physical attendance wide uh wide.

Final Reflections And Thanks

SPEAKER_01 48:03

Well, Benoit, your career has been amazing. And I uh, you know, I've I've been around academia and supply chain for my career as well, and I was so impressed with the institute that you've created and are running. Uh congratulations on your amazing success uh in your career and all the people you've helped, people and companies. Um I really think uh professors should aspire to that. Um but also thank you for taking time to visit with me. I've really considered it an honor uh to be able to visit with you about this.

SPEAKER_00 48:44

Matt, thank you for these kind words. Okay. I just want to mention that uh I could never have done that alone. Okay. It's uh I've had the help of so many students, so many colleagues, okay, so many people from industry that have helped through this. It's a it's it's all team effort and this and uh and getting the synergy and all that, because otherwise, if I if we play solo, it's never gonna work. So it's uh it's a work in process, okay. Even though I'm getting later in age, okay, it's still there's still so much to do. And if I can be inspiring a few uh people to uh to think differently and get the courage and the the inspiration to to move forward in these kind of new ways, okay. Uh I think this will be good for me. Uh I appreciate very much you inviting me here, and hopefully this will be uh uh good value to your audience.